CN106292292A - The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning - Google Patents

The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning Download PDF

Info

Publication number
CN106292292A
CN106292292A CN201610902747.5A CN201610902747A CN106292292A CN 106292292 A CN106292292 A CN 106292292A CN 201610902747 A CN201610902747 A CN 201610902747A CN 106292292 A CN106292292 A CN 106292292A
Authority
CN
China
Prior art keywords
case
value
floatation
flotation
iron ore
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201610902747.5A
Other languages
Chinese (zh)
Inventor
张明
高宪文
杨光
王明顺
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Angang Group Mining Co Ltd
Original Assignee
Angang Group Mining Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Angang Group Mining Co Ltd filed Critical Angang Group Mining Co Ltd
Priority to CN201610902747.5A priority Critical patent/CN106292292A/en
Publication of CN106292292A publication Critical patent/CN106292292A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Manufacture And Refinement Of Metals (AREA)

Abstract

The present invention provides the floatation of iron ore dosing Optimal Setting method and system of a kind of case-based reasioning, and the method includes: extract historical data from floatation of iron ore production process；Building floatation of iron ore case library, be that case describes by flotation boundary condition and technic index desired value, floating agent dosage is that case illustrates；In case library, carry out Case Retrieval, obtain one group of Similarity value；Similarity value is arranged from big to small, chooses case corresponding to front n Similarity value and describe the reference case description as current working；Case is reused the new case of acquisition and is illustrated；When error is more than Case-based adaptation when setting threshold value, generate new case；Case Retrieval finds the case with new case to describe the case description with maximum similarity value, completes case library and updates.The creation data surveyed that the present invention is correlated with by means of floatation of iron ore dosing, provides the dosing setting value being applicable to various operating mode, can improve safety, reliability and economy that floatation of iron ore produces.

Description

The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning
Technical field
The invention belongs to floatation of iron ore technical field, be specifically related to the floatation of iron ore dosing of a kind of case-based reasioning Optimal Setting method and system.
Background technology
In floatation of iron ore production process, rational regime of agent can be effectively improved concentrate grade and reduce mine tailing product simultaneously Position.At present regime of agent relies on artificial experience to be adjusted mostly, but the operator that enriches not of experience or operator Maloperation be likely to make the regime of agent of mistake, and in most cases regime of agent keeps not within a certain period of time Becoming, above-mentioned situation will certainly cause useful component in ore pulp the most sufficiently to be sorted or medicament excess, causes iron mine to float Select inefficiency, cause the wasting of resources.Minority iron ore beneficiating factory uses automatic medicament feeding machine to carry out medicament control, but automatic medicament feeding machine Expensive and maintenance cost is high, increase beneficiation cost.
Summary of the invention
The deficiency existed for prior art, the present invention provides the floatation of iron ore dosing of a kind of case-based reasioning excellent Change establishing method and system.
A kind of floatation of iron ore dosing Optimal Setting method of case-based reasioning, comprises the steps:
Step 1: extract historical data from floatation of iron ore production process, including floating agent dosage, flotation boundary condition And technic index desired value；
Described flotation boundary condition, including: to ore deposit grade, feed ore concentration, flotation temperature；
Described technic index desired value: Floatation Concentrate Grade desired value, flotation tailing grade desired value, flotation recovery rate mesh Scale value；
Step 2: according to the historical data obtained, builds floatation of iron ore case library, by flotation boundary condition and technic index Desired value is that case describes, and floating agent dosage is that case illustrates, and case describes and is deconstructed into case with case；
Step 3: using the flotation boundary condition obtained in real time in floatation of iron ore production process and technic index desired value as New case describes, and carries out Case Retrieval in case library, obtains new case description and retouches with each case described in case library One group of Similarity value between stating；
Step 4: arranged from big to small by Similarity value, the case chosen in the case library that front n Similarity value is corresponding is retouched State the reference case as current working to describe；
Step 5: describe according to the reference case being retrieved from case library, carry out case and reuse, it is thus achieved that new case Solve, i.e. for the floating agent dosage setting value of current working；
Step 6: by the actual laboratory values of Floatation Concentrate Grade and Floatation Concentrate Grade desired value, the reality of flotation tailing grade Border laboratory values compares with flotation recovery rate desired value with the Practical Calculation value of flotation tailing grade desired value, flotation recovery rate And calculate the absolute value of error, when error is more than when setting threshold value, by the actual laboratory values of Floatation Concentrate Grade, flotation tailing product Position actual laboratory values, flotation recovery rate Practical Calculation value as new case case describe in technic index desired value, Complete Case-based adaptation, generate new case；
Step 7: the case of new case generated is described in case library and carries out Case Retrieval, find the case with new case The case that example describes in the case library with maximum similarity value describes, if this maximum similarity value is more than similarity threshold, then Giving up the new case of generation, otherwise, the case replaced in this case library with maximum similarity value with the new case generated is retouched State, complete the renewal of case library.
Described step 5, specifically comprises the following steps that
Step 5.1: judge the maximum similarity value between each reference case description of new case description and current working, be No more than the similarity threshold set, it is then to perform step 5.2, otherwise, that asks for that every kind of case of n reference case illustrates adds Weight average value illustrates as new case, completes case and reuses, and then performs step 6；Ask for the weighting used during weighted mean Coefficient is that each case describes the Similarity value described with new case；
Step 5.2: case corresponding for maximum similarity value is illustrated and is set to new case and illustrates, complete case and reuse, then hold Row step 6.
The floatation of iron ore medicament that the floatation of iron ore dosing Optimal Setting method of described case-based reasioning uses is used Amount Optimal Setting system, including:
Flotation boundary condition and the data acquisition module of technic index desired value is obtained in real time in floatation of iron ore production process Block；
Receive flotation boundary condition and technic index desired value and be forwarded to the wireless Zigbee transmission of Ethernet industrial computer Module；
Receive flotation boundary condition and technic index desired value and be forwarded to the ether of dosing Optimal Setting computer Net industrial computer；
Receive the data that Ethernet industrial computer sends the dosing optimization carrying out dosing Optimal Setting and display Setting computer；
The outfan of data acquisition module connects the input of wireless Zigbee transmission module, wireless Zigbee transmission module Outfan connect the input of Ethernet industrial computer, the outfan of Ethernet industrial computer connects dosing Optimal Setting and calculates The input of machine.
Beneficial effect:
The floatation of iron ore dosing Optimal Setting method of the case-based reasioning of the present invention and present manual adjustment medicine Agent institutional method compares and has the advantage that the surveyed creation data relevant by means of floatation of iron ore dosing, is given It is applicable to the dosing setting value of various operating mode, safety, reliability and economy that floatation of iron ore produces can be improved.Carry High flotation production efficiency, reduces the probability made mistakes.Have the advantage that, compared with flotation dosing machine, the equipment of decreasing Maintenance cost, reduce production cost；Field data automatically saves, it is not necessary to manual record, reduces loss of data, record mistake Probability by mistake.
Accompanying drawing explanation
Fig. 1 is the floatation of iron ore dosing Optimal Setting method stream of case-based reasioning in the specific embodiment of the invention Cheng Tu；
Fig. 2 is step 5 flow chart in the specific embodiment of the invention；
Fig. 3 is floatation of iron ore dosing Optimal Setting system block diagram in the specific embodiment of the invention.
Detailed description of the invention
It is embodied as elaborating to the present invention below in conjunction with the accompanying drawings.
A kind of floatation of iron ore dosing Optimal Setting method of case-based reasioning, as it is shown in figure 1, include walking as follows Rapid:
Step 1: extract historical data from floatation of iron ore production process, including floating agent dosage, flotation boundary condition And technic index desired value, such as table 1:
Table 1 historical data
In conjunction with historical data, production scene investigation and floatation process theory analysis, above-mentioned flotation boundary condition and technique refer to Mark target value data has directly impact to floating agent dosage, and proportion is very big, straight to ore deposit grade, feed ore concentration Connect the consumption collocation affecting in floating agent between variety classes medicament；Flotation time and flotation temperature affect sending out of floating agent Wave effect.
Step 2: according to the historical data obtained, builds floatation of iron ore case library, by flotation boundary condition and technic index Desired value is that case describes, and floating agent dosage is that case illustrates, and case describes and is deconstructed into case with case；
In order to obtain the setting value of floating agent dosage, need first to consider Floatation Concentrate Grade desired value, flotation tailing Grade desired value, flotation recovery rate desired value, next to that current working condition.The structure of case is described by case and case illustrates Two parts form, and it is by technic index desired value (Floatation Concentrate Grade desired value z that case describes1, flotation tailing grade desired value z2, response rate desired value z3) and flotation boundary condition (to ore deposit grade z4, feed ore concentration z5, flotation time z6, flotation temperature z7) group Become；Case illustrates as floating agent dosage setting value x1。
The case of case-based reasioning technology can be expressed as follows:
Ck={ Fk, Jk}
In formula: Ck(k=1 ..., m) represent kth bar case, m is growing number；Fk={ zk.1, zk.2, zk.3, zk.4, zk.5, zk.6, zk.7It is that kth case describes, case is described and is abbreviated as Fk={ fk.1..., fk.7}；Jk={ xk.1It it is kth case Case illustrate, case is illustrated and is abbreviated as Jk。
Step 3: using the flotation boundary condition obtained in real time in floatation of iron ore production process and technic index desired value as New case describes F, carries out Case Retrieval in case library, obtains new case description and retouches with each case described in case library One group of Similarity value between stating, similarity is the number between 0 to 1, such as 0.88；
S I M ( F , F k ) = Σ k = 1 m Σ i = 1 7 ω i S I M ( f i , f k . i ) Σ i = 1 7 ω i
Wherein, ωiThe weights described for case, m is the case number of cases in case library, SIM (fi, fk.i) it is the case of current working Example describes fiThe case corresponding with kth bar case in case library describes fk.iSimilarity, be defined as:
S I M ( f i , f k . i ) = 1 - | f i - f k . i | m a x ( f i , f k . i ) , i ≠ 7 1 - | f i - f k . i | 3 , i = 7
Step 4: arranged from big to small by Similarity value, the case chosen in the case library that front n Similarity value is corresponding is retouched State the reference case as current working to describe；
The selection of n value can produce significant impact to result, and n value is less to be meaned only to be closer to new case description History case describes just to illustrate new case and works, but is susceptible to over-fitting；If n value is relatively big, describe with new case Prediction also can be worked by the history case relatively kept off, and makes prediction make a mistake.In actual applications, n value is typically chosen one Individual less numerical value, generally uses the method for cross validation to select the n value of optimum, and the value of n is 3 in the present embodiment；
Step 5: describe according to the reference case being retrieved from case library, carry out case and reuse, it is thus achieved that new case Solve, i.e. for the floating agent dosage setting value of current working, such as table 2:
The case that table 2 is new illustrates
Title Consumption
Collecting agent (is roughly selected) 130ml/s
Collecting agent (selected) 90ml/s
NaOH 85ml/s
CaO 1000ml/s
Starch 500ml/s
Described step 5, as in figure 2 it is shown, specifically comprise the following steps that
Step 5.1: judge the maximum similarity value between each reference case description of new case description and current working, be No more than the similarity threshold set, it is then to perform step 5.2, otherwise, that asks for that every kind of case of n reference case illustrates adds Weight average value illustrates as new case, completes case and reuses, and then performs step 6；Ask for the weighting used during weighted mean Coefficient is that each case describes the Similarity value described with new case；
The concrete value of similarity threshold depends on the quantity of history case in case library, if the quantity of history case is c, Similarity threshold is v, if c ＜ 200, v=0.9；If 200 ＜ c ＜ 500, v=0.8；If c ＞ 500, v=0.7.
Step 5.2: case corresponding for maximum similarity value is illustrated and is set to new case and illustrates Completing case to reuse, then perform step 6, wherein, the case that J is new illustrates, JkCase for reference case illustrates, and n is with reference to case The quantity of example.
Step 6: by the actual laboratory values of Floatation Concentrate Grade and Floatation Concentrate Grade desired value, the reality of flotation tailing grade Border laboratory values compares with flotation recovery rate desired value with the Practical Calculation value of flotation tailing grade desired value, flotation recovery rate And calculate the absolute value of error, when error is more than when setting threshold value 5%, by the actual laboratory values of Floatation Concentrate Grade, flotation tail The actual laboratory values of ore deposit grade, flotation recovery rate Practical Calculation value as new case case describe in technic index target Value, completes Case-based adaptation, generates new case；
The definition actual laboratory values of concentrate grade, the actual laboratory values of tailings grade are respectively βkAnd βw(such as 68.62 Hes 28.88), the Practical Calculation value of flotation recovery rate is α, and the bound of concentrate grade desired value is respectively βe.k max、βe.k min(as 70.00 and 65.00), the upper limit of tailings grade desired value is βe.w max(such as 23.00), the bound of flotation recovery rate desired value It is respectively αe max、αe min, meet following formula and error and be not more than and set threshold value 5%:
β e . k min ≤ β k ≤ β e . k m a x β w ≤ β e . w m a x α e min ≤ α ≤ α e max
The most directly proceeding to case storage, be otherwise modified case, Case-based adaptation uses empirical method, until actual value Enter target range.
Step 7: the case of new case generated is described in case library and carries out Case Retrieval, find the case with new case The case that example describes in the case library with maximum similarity value describes, if this maximum similarity value is more than similarity threshold, then Giving up the new case of generation, otherwise, the case replaced in this case library with maximum similarity value with the new case generated is retouched State, complete the renewal of case library.
The floatation of iron ore medicament that the floatation of iron ore dosing Optimal Setting method of described case-based reasioning uses is used Amount Optimal Setting system, as it is shown on figure 3, include:
Flotation boundary condition and the data acquisition module of technic index desired value is obtained in real time in floatation of iron ore production process Block；
Receive flotation boundary condition and technic index desired value and be forwarded to the wireless Zigbee transmission of Ethernet industrial computer Module；
Receive flotation boundary condition and technic index desired value and be forwarded to the ether of dosing Optimal Setting computer Net industrial computer；
Receive the data that Ethernet industrial computer sends the dosing optimization carrying out dosing Optimal Setting and display Setting computer, is shown the dosing set by human-computer interaction interface；
The outfan of data acquisition module connects the input of wireless Zigbee transmission module, wireless Zigbee transmission module Outfan connect the input of Ethernet industrial computer, the outfan of Ethernet industrial computer connects dosing Optimal Setting and calculates The input of machine.

Claims (3)

1. the floatation of iron ore dosing Optimal Setting method of a case-based reasioning, it is characterised in that: comprise the steps:
Step 1: extract historical data from floatation of iron ore production process, including floating agent dosage, flotation boundary condition and work Skill target goals value；
Described flotation boundary condition, including: to ore deposit grade, feed ore concentration, flotation temperature；
Described technic index desired value: Floatation Concentrate Grade desired value, flotation tailing grade desired value, flotation recovery rate target Value；
Step 2: according to the historical data obtained, builds floatation of iron ore case library, by flotation boundary condition and technic index target Being worth and describe for case, floating agent dosage is that case illustrates, and case describes and is deconstructed into case with case；
Step 3: using the flotation boundary condition obtained in real time in floatation of iron ore production process and technic index desired value as new Case describes, and carries out Case Retrieval in case library, obtains new case description and describes it with each case described in case library Between one group of Similarity value；
S I M ( F , F k ) = Σ k = 1 m Σ i = 1 7 ω i S I M ( f i , f k . i ) Σ i = 1 7 ω i
Wherein, ωiThe weights described for case, m is the case number of cases in case library, SIM (fi, fk.i) it is that the case of current working is retouched State fiThe case corresponding with kth bar case in case library describes fk.iSimilarity, be defined as:
S I M ( f i , f k . i ) = 1 - | f i - f k . i | m a x ( f i , f k . i ) , i ≠ 7 1 - | f i - f k . i | 3 , i = 7
Step 4: arranged from big to small by Similarity value, chooses the case in the case library that front n Similarity value is corresponding and describes work Reference case for current working describes；
Step 5: describe according to the reference case being retrieved from case library, carry out case and reuse, it is thus achieved that new case illustrates, i.e. Floating agent dosage setting value for current working；
Step 6: by the actual laboratory values of Floatation Concentrate Grade and Floatation Concentrate Grade desired value, actualization of flotation tailing grade The Practical Calculation value testing value and flotation tailing grade desired value, flotation recovery rate compares with flotation recovery rate desired value and counts Calculate the absolute value of error, when error is more than when setting threshold value, by the actual laboratory values of Floatation Concentrate Grade, flotation tailing grade Actual laboratory values, flotation recovery rate Practical Calculation value as new case case describe in technic index desired value, complete Case-based adaptation, generates new case；
Step 7: the case of new case generated is described in case library and carries out Case Retrieval, find the case with new case to retouch State the case in the case library with maximum similarity value to describe, if this maximum similarity value is more than similarity threshold, then give up The new case generated, otherwise, replaces the case in this case library with maximum similarity value with the new case generated and describes, complete Become the renewal of case library.
The floatation of iron ore dosing Optimal Setting method of case-based reasioning the most according to claim 1, its feature exists In: described step 5, specifically comprise the following steps that
Step 5.1: judge the maximum similarity value between each reference case description of new case description and current working, if big In the similarity threshold set, it is then to perform step 5.2, otherwise, asks for the weighting that every kind of case of n reference case illustrates flat Average illustrates as new case, completes case and reuses, and then performs step 6；Ask for the weight coefficient used during weighted mean The Similarity value described with new case is described for each case；
Step 5.2: case corresponding for maximum similarity value is illustrated and is set to new case and illustrates, complete case and reuse, then perform step Rapid 6.
3. the iron mine that the floatation of iron ore dosing Optimal Setting method of case-based reasioning as claimed in claim 1 uses floats Select dosing Optimal Setting system, it is characterised in that including:
Flotation boundary condition and the data acquisition module of technic index desired value is obtained in real time in floatation of iron ore production process；
Receive flotation boundary condition and technic index desired value and be forwarded to the wireless Zigbee transmission module of Ethernet industrial computer；
Receive flotation boundary condition and technic index desired value and be forwarded to the Ethernet work of dosing Optimal Setting computer Control machine；
Receive the data that Ethernet industrial computer sends the dosing Optimal Setting carrying out dosing Optimal Setting and display Computer；
The outfan of data acquisition module connects the input of wireless Zigbee transmission module, wireless Zigbee transmission module defeated Going out end and connect the input of Ethernet industrial computer, the outfan of Ethernet industrial computer connects dosing Optimal Setting computer Input.
CN201610902747.5A 2016-10-17 2016-10-17 The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning Pending CN106292292A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610902747.5A CN106292292A (en) 2016-10-17 2016-10-17 The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610902747.5A CN106292292A (en) 2016-10-17 2016-10-17 The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning

Publications (1)

Publication Number Publication Date
CN106292292A true CN106292292A (en) 2017-01-04

Family

ID=57717522

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610902747.5A Pending CN106292292A (en) 2016-10-17 2016-10-17 The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning

Country Status (1)

Country Link
CN (1) CN106292292A (en)

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107038481A (en) * 2017-03-29 2017-08-11 北京科技大学 A kind of case-based reasoning system building method towards metallurgical mine field
CN108469797A (en) * 2018-04-28 2018-08-31 东北大学 A kind of grinding process modeling method based on neural network and evolutionary computation
CN109569887A (en) * 2018-11-23 2019-04-05 鞍钢集团矿业有限公司 A kind of floatation of iron ore dosing autocontrol method based on tailings grade
CN110193427A (en) * 2019-06-19 2019-09-03 北京矿冶科技集团有限公司 A kind of autocontrol method of copper flotation flowsheet lime-crushed stone pile
CN110928183A (en) * 2019-11-13 2020-03-27 鞍钢集团矿业有限公司 Fuzzy control method for flotation concentrate grade
CN111198550A (en) * 2020-02-22 2020-05-26 江南大学 Cloud intelligent production optimization scheduling on-line decision method and system based on case reasoning
CN113003692A (en) * 2021-03-05 2021-06-22 北京工业大学 Case reasoning-based dosing control method for denitrification process of municipal sewage treatment
CN113064390A (en) * 2021-03-17 2021-07-02 国网辽宁省电力有限公司辽阳供电公司 Case reasoning-based active warning method for pollutant emission of cement production enterprise
CN117427770A (en) * 2023-08-18 2024-01-23 内蒙古兴业集团融冠矿业有限公司 Intelligent control method and system for mineral separation

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5581664A (en) * 1991-03-04 1996-12-03 Inference Corporation Case-based reasoning system
CN1603986A (en) * 2004-10-29 2005-04-06 东北大学 Grinding system intelligent optimization initialization method based on case ratiocination
CN1749891A (en) * 2005-10-19 2006-03-22 东北大学 Intelligent optimized control method for comprehensive production index in ore dressing process
CN103061750A (en) * 2013-01-25 2013-04-24 东北大学 Online measuring method for dynamic liquid level under sucker rod oil well
CN104318313A (en) * 2014-09-19 2015-01-28 东北大学 Intelligent decision system and method for ore dressing total flow operation index on the basis of case-based reasoning

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5581664A (en) * 1991-03-04 1996-12-03 Inference Corporation Case-based reasoning system
CN1603986A (en) * 2004-10-29 2005-04-06 东北大学 Grinding system intelligent optimization initialization method based on case ratiocination
CN1749891A (en) * 2005-10-19 2006-03-22 东北大学 Intelligent optimized control method for comprehensive production index in ore dressing process
CN103061750A (en) * 2013-01-25 2013-04-24 东北大学 Online measuring method for dynamic liquid level under sucker rod oil well
CN104318313A (en) * 2014-09-19 2015-01-28 东北大学 Intelligent decision system and method for ore dressing total flow operation index on the basis of case-based reasoning

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
李海波 等: "浮选过程混合智能优化设定控制方法", 《东北大学学报(自然科学版)》 *
耿增显 等: "基于案例推理的浮选过程智能优化设定", 《东北大学学报(自然科学版)》 *

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107038481A (en) * 2017-03-29 2017-08-11 北京科技大学 A kind of case-based reasoning system building method towards metallurgical mine field
CN108469797A (en) * 2018-04-28 2018-08-31 东北大学 A kind of grinding process modeling method based on neural network and evolutionary computation
CN108469797B (en) * 2018-04-28 2020-09-29 东北大学 Neural network and evolutionary computation based ore grinding process modeling method
CN109569887A (en) * 2018-11-23 2019-04-05 鞍钢集团矿业有限公司 A kind of floatation of iron ore dosing autocontrol method based on tailings grade
CN110193427A (en) * 2019-06-19 2019-09-03 北京矿冶科技集团有限公司 A kind of autocontrol method of copper flotation flowsheet lime-crushed stone pile
CN110928183A (en) * 2019-11-13 2020-03-27 鞍钢集团矿业有限公司 Fuzzy control method for flotation concentrate grade
CN110928183B (en) * 2019-11-13 2022-09-16 鞍钢集团矿业有限公司 Fuzzy control method for flotation concentrate grade
CN111198550A (en) * 2020-02-22 2020-05-26 江南大学 Cloud intelligent production optimization scheduling on-line decision method and system based on case reasoning
CN113003692A (en) * 2021-03-05 2021-06-22 北京工业大学 Case reasoning-based dosing control method for denitrification process of municipal sewage treatment
CN113064390A (en) * 2021-03-17 2021-07-02 国网辽宁省电力有限公司辽阳供电公司 Case reasoning-based active warning method for pollutant emission of cement production enterprise
CN113064390B (en) * 2021-03-17 2022-03-01 国网辽宁省电力有限公司辽阳供电公司 Case reasoning-based active warning method for pollutant emission of cement production enterprise
CN117427770A (en) * 2023-08-18 2024-01-23 内蒙古兴业集团融冠矿业有限公司 Intelligent control method and system for mineral separation

Similar Documents

Publication Publication Date Title
CN106292292A (en) The floatation of iron ore dosing Optimal Setting method and system of case-based reasioning
CN104835074A (en) Ore blending method of strip mine production
CN102609714B (en) Novel classification device and sorting technique based on information gain and Online SVM
CN105974794A (en) Discrete manufacture workshop scheduling method based on improved cat group algorithm
CN110288237B (en) Implementation method of dynamically configurable mineral processing technological process
CN113130014B (en) Rare earth extraction simulation method and system based on multi-branch neural network
CN104597755A (en) Hydrometallurgical gold cyanide leaching optimization method
CN105643157A (en) Automatic girder welding obstacle predicting method for optimizing GRNN based on correction type fruit fly algorithm
CN105740521A (en) Small grid removing method and apparatus in oil reservoir numerical simulation system solution process
CN104460590B (en) Semiconductor production line multi-product workpiece combining method
CN103164752A (en) Heuristic one-dimensional blanking method based on stratified random search algorithm
CN109933843A (en) Intelligent reinforcing bar based on BIM covers blanking construction method
CN103617456A (en) Operating index optimization method in beneficiation process
CN111079978A (en) Coal and gas outburst prediction method based on logistic regression and reinforcement learning
CN106406257B (en) A kind of the floatation of iron ore concentrate grade flexible measurement method and system of case-based reasioning
CN109669030A (en) A kind of industrial injecting products defect diagnostic method based on decision tree
CN104281134B (en) System and method for optimizing multiple production indexes in sorting process of raw ore based on man-machine interaction
CN104318313A (en) Intelligent decision system and method for ore dressing total flow operation index on the basis of case-based reasoning
CN104503382A (en) Raw material crystallization process optimization scheduling method for pharmaceutical chemical production
JP2016024610A (en) Product collection plan creation method and product collection plan creation device
CN103439964B (en) A kind of online updating system and method for OCSVM monitoring model
CN105718426A (en) Dredging output mathematical model building method based on multiple linear regression analysis
CN103221816B (en) Comprise the method and apparatus of the flotation separation processing controls of the parameter that flotation process and reagent for optimizing mineral recovery are added
CN102819237A (en) Method for generating simulation target blank in solid milling simulation process
CN107392978A (en) Oil well development method and apparatus

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20170104